The most popular estimation techniques for image warping in real practice are nearest neighbour, bilinear and bicubic (spline) interpolation schemes [1]}, which do not adapt well to irregular image regions. Therefore, academic research effort has been mainly dedicated to edge guided interpolation, such as anisotropic filtering (e.g., [2]}, [3]}) and variational regularization (e.g., [4]}). Particularly on the sub-topic of Signal Image Super-resolution, i.e., in the special case that \(\mathbf {H}\)  degenerates to a scaling function, mathematical models such as compressive sensing (e.g., [5]}), dictionary learning (e.g., [6]}) and Convolutional Neural Networks (CNN, e.g., [7]}) have also been intensively investigated.
